As users move more towards digital and digitally recordable means of communications, it is becoming easier to monitor the communications of large groups of people, such as employees. This can be particularly beneficial to companies that wish to evaluate the performance and behaviours of their employees through automated means.
However, while systems are available to automatically log and record phone calls, emails and chat messages within office environments, existing methods of processing these large volumes of data are computationally expensive and typically require a high degree of human intervention. Many companies are now in a position where they are overloaded with communication-related data, but have neither the computational hardware nor the time to process the data in a meaningful way.
Determining whether a user is communicating with a client or a friend, for example, either requires prior user-input identifying which correspondents are work-related, or requires computationally expensive natural language processing (NLP) systems to understand and process the content of communications.
There is therefore a need for a computationally efficient means of monitoring communications between correspondents and automatically evaluating the nature of the communications and the relationships between the correspondents. There is also a need for a user interface to enable a user to interact with and visualise the large amounts of data available in a meaningful format.